Prefrontal cortex structural and developmental associations with callous-unemotional traits and aggression
Bibliographic record
Abstract
Youths with high levels of callous-unemotional (CU) traits and aggression are at an increased risk for developing antisocial behaviours into adulthood. In this population, neurostructural grey matter abnormalities have been observed in the prefrontal cortex. However, the directionality of these associations is inconsistent, prompting some to suggest they may vary across development. Although similar neurodevelopmental patterns have been observed for other disorders featuring emotional and behavioural dysregulation, few studies have tested this hypothesis for CU traits, and particularly not for aggression subtypes. The current study sought to examine grey matter correlates of CU traits and aggression (including its subtypes), and then determine whether these associations varied by age. Fifty-four youths (10-19 years old) who were characterized for CU traits and aggression underwent MRI. Grey matter volume and surface area within the anterior cingulate cortex was positively associated with CU traits. The correlation between CU traits and medial orbitofrontal cortex (mOFC) volume varied significantly as a function of age, as did the correlation between reactive aggression and mOFC surface area. These associations became more positive with age. There were no significant findings for proactive/total aggression. Results are interpreted considering the potential for delayed cortical maturation in youths with high CU traits/aggression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".